UAV-based solar photovoltaic detection dataset

This dataset contains unmanned aerial vehicle (UAV) imagery (a.k.a. drone imagery) and annotations of solar panel locations captured from controlled flights at various altitudes and speeds across two sites at Duke Forest (Couch field and Blackwood field). In total there are 423 stationary images and corresponding annotations of solar panels within sight, along with 60 videos taken from flying the UAV roughly at either 8 m/s or 14 m/s. In total there are 2,019 solar panel instances annotated.<b><br></b>Associated publication:<b><br></b>“Utilizing geospatial data for assessing energy security: Mapping small solar home systems using unmanned aerial vehicles and deep learning” [https://arxiv.org/abs/2201.05548]<b><br></b>Data processing:<b><br></b>Please refer to this Github repository for further details on data management and preprocessing: https://github.com/BensonRen/Drone_based_solar_PV_detection. The two scripts included enable the user to reproduce the experiments in the paper above.<b><br></b>Contents:<b><br></b>After unzipping the package, there will be 3 directories:<b><br></b>1. Train_val_set: Stationary UAV images (.JPG) taken at various altitudes in the Couch field of Duke Forest for training and validation purposes, along with their solar PV annotations (.png)<b><br></b>2. Test_set: Stationary UAV images (.JPG) taken at various altitudes in the Blackwood field of Duke Forest for test purposes, along with their solar PV annotations (.png)<b><br></b>3. Moving_labeled: Images (img/*.png) capture from videos moving with two speed modes (Sport: 14m/s, Norma: 8m/s) at various altitudes and their solar PV annotations (labels/*.png)<b><br><br><br></b>For additional details of this dataset, please refer to REAMDE.docx enclosed.<b><br><br></b>Acknowledgments: This dataset was created at the Duke University Energy Initiative in collaboration with the Energy Access Project at Duke and RTI International. We thank the Duke University Energy Data Analytics Ph.D. Student Fellowship Program for their support. We also thank Duke Forest for use of the flight zones for data collection.<br>